class_docstr: A class representing a mean scaling approach. Inputs are simply rescaled
  based on their mean.
  
  Parameters
  ----------
  minimum_scale
      The minimum value to which re-scaled values will be clipped to.
      (default: 1e-10)
  clip_max
      The maximum value to which re-scaled values will be clipped to.
      Negative values will be clipped at -clip_max and positive values at
      clip_max. (default: None)
code: def __init__(
      self,
      scale_min: float = 1e-10,
      clip_max: Optional[float] = None,
      *args,
      **kwargs,
  ):
      super().__init__(*args, **kwargs)
      self.scale_min = scale_min
      self.clip_max = clip_max
  
file_path: gluonts/src/gluonts/mx/representation/mean_scaling.py
imports: from typing import List, Optional, Tuple
  from gluonts.core.component import validated
  from gluonts.mx import Tensor
  from .representation import Representation
label_desc: Use image node_id 1 to create a new MeanScaling object from inherited base classes: Representation with example: obj = MeanScaling(scale_min, clip_max)